Journal of computational biology : a journal of computational molecular cell biology | 2019

Transcriptional Regulatory Network Analysis to Reveal the Key Genes Involved in Skeletal Muscle Injury

 
 

Abstract


Skeletal muscle is among the three major muscle types, and skeletal muscle injury (SMI) can elevate the risk of dependency and falls. This study is designed to explore the key genes involved in SMI and skeletal muscle regeneration. Microarray data set GSE81096, which included 11 injured skeletal muscle stem cell samples and 12 noninjured skeletal muscle stem cell samples, was from Gene Expression Omnibus. The differentially expressed genes (DEGs) between injured and noninjured samples were screened by R package limma, and then were performed with enrichment analysis based on the Database for Annotation, Visualization, and Integrated Discovery. Followed by protein-protein interaction (PPI), transcriptional regulatory analyses were conducted using Cytoscape software. A total of 1018 DEGs were screened from the injured samples, among which four upregulated genes and nine downregulated genes were predicted as transcription factors. Besides, four modules were identified from the PPI network. In the transcriptional regulatory network, E2F1, E2F4, JUNB, FOS, and MEF2C had higher degrees. Moreover, E2F4 and FOS might function in SMI separately through targeting E2F1 and JUNB. E2F1, E2F4, JUNB, FOS, and MEF2C might be involved in SMI and skeletal muscle regeneration.

Volume None
Pages None
DOI 10.1089/cmb.2019.0025
Language English
Journal Journal of computational biology : a journal of computational molecular cell biology

Full Text